Clustering of high-throughput sequencing data by identifying co-expression patterns


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Documentation for package ‘clusterSeq’ version 1.20.0

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clusterSeq-package Clustering of high-throughput sequencing data by identifying co-expression patterns
associatePosteriors Associates posterior likelihood to generate co-expression dissimilarities between genes
cD.ratThymus Data from female rat thymus tissue taken from the Rat BodyMap project (Yu et al, 2014) and processed by baySeq.
clusterSeq Clustering of high-throughput sequencing data by identifying co-expression patterns
kCluster Constructs co-expression dissimilarities from k-means analyses.
makeClusters Creates clusters from a co-expression minimal linkage data.frame.
makeClustersFF Creates clusters from a file containing a full dissimilarity matrix.
plotCluster Plots data from clusterings.
ratThymus Data from female rat thymus tissue taken from the Rat BodyMap project (Yu et al, 2014).
wallace Computes Wallace scores comparing two clustering methods.